DIPLOMARBEIT Titel der Diplomarbeit Nitrogen-source related effects on drought stress response in Medicago truncatula Verfasserin: Christiana Elisabeth Staudinger angestrebter akademischer Grad Magistra der Naturwissenschaften (Mag. rer. nat) Wien, im Oktober 2010 Matrikelnummer: 0501998 Studienkennzahl lt. Studienblatt: A438 Studienrichtung lt. Studienblatt: Botanik Betreuer: Univ.-Prof. Dr. Wolfram Weckwerth Contents 1. Introduction 11 1.1. Legumes and Medicago truncatula ....................... 11 1.2. Mass spectrometry-based proteomics...................... 12 1.3. General objectives of this work......................... 13 2. Material and Methods 15 2.1. Experimental setup................................ 15 2.2. Cultivation.................................... 15 2.3. Stomatal density and index........................... 16 2.4. Stomatal conductance.............................. 17 2.5. Chlorophyll fluorometry............................. 17 2.6. Nitrogen and carbon isotopic signatures.................... 17 2.7. Leaf protein extraction and MS analysis.................... 18 2.8. Data mining.................................... 19 3. Results 21 3.1. Physiological measurements........................... 21 3.2. Proteomic analyses................................ 22 4. Discussion 29 4.1. Physiological determination of drought stress levels.............. 29 4.2. Integrative physiological and proteomic comparison.............. 29 4.2.1. Phenotyping: Similarities and differences of the leaf depending on N-source.................................. 29 4.2.2. Differential response to drought and evidence for increased tolerance of symbiotic plants............................ 31 4.2.3. Putative marker and future evaluation strategies........... 31 5. Summary 37 6. Acknowledgments 41 A. AttachmentI A.1. Physiological and proteomic supplemental data................I A.2. Formulations...................................XV A.3. Curriculum vitae.................................XV 3 List of Figures 2.1. Experimental setup................................ 15 3.1. Stomatal density................................. 21 3.2. PCA of day 6 proteins.............................. 23 4.1. Spectral counts of Mg-chelatase isoform-specific peptide ions........ 32 4.2. Metabolic context of symbiotic stress response................ 35 4.3. Metabolic context of N-fed stress response................... 36 A.1. Substrate water content.............................I A.2. Photosystem II operating efficiency....................... II A.3. Shoot and root δ15N signatures......................... II A.4. Shoot and root δ13C ............................... II 5 List of Tables 2.1. Types of measurements and their timepoints.................. 16 3.1. Stable isotope concentrations and root/shoot ratios in response to drought. 22 3.2. Drought responsive proteins in symbiotic plants................ 26 3.3. Drought responsive proteins in N-fed plants.................. 28 4.1. Significantly different proteins in controls................... 34 A.1. Stomatal density and index...........................I A.2. Stomatal conductance gs on days 3 and 6...................I A.4. TY-0.8%Agar Medium..............................XV A.5. TY Medium....................................XV 7 List of Abbreviations AAA+ ATPase associated with various cellular activities ABA abscisic acid ACC acetly-CoA carboxylase ACN acetonitrile ANOVA analysis of variance BCKDC branched chain α-keto acid dehydrogenase complex CHL P geranylgeranyl reductase (unit P of procaryote chlorophyll synthase) CHR chalcone reductase CID collision induced dissociation clp chloroplast db database ED density of epidermal pavement cells ESI electrospray ionisation EST expressed sequence tag FA formic acid FqFm photosystem II operating efficiency Glu1P glucose-1-phosphate gs stomatal conductance IAA indole acetic acid IPP isopentenyl diphosphate MEP/DOXP 2-C-methyl-D-erythritol 4-phosphate/1-deoxy-D-xylulose 5-phosphate MIPS myo-inositol-1-phosphate synthase MS mass spectrometry MS/MS tandem mass spectrometry mt mitochondrial MtGI Medicago truncatula Gene Index N-fed nitrate fertilized OGDC 2-oxoglutarate dehydrogenase complex PC principal component PCA principal component analysis 9 List of Tables PDC pyruvate dehydrogenase complex PPFD photosynthetically active photon flux density prec precursor ProMEX protein mass spectra extraction PSII photosystem II R isotope ratio rpm runs per minute RWC relative water content SAM S-adenosylmethionine SC spectral count SD stomatal density SE standard error SHMT serine hydroxymethyltransferase SI stomatal index SPEC solid phase extraction cartridges Sym symbiotic TC tentative consensus TCA tricarbonic acid 10 1. Introduction 1.1. The legume family and the model organism Medicago truncatula Legumes evolved during the early Tertiary period, approximately 60 million years ago [28]. Today they are ubiquitous elements of most of the worlds biomes in the form of annuals, shrubs, vines, lianas, trees and even some aquatic life-forms. Third to Orchidaceae and Asteraceae, the Leguminosae constitute with 20 000 plant species [29] one of the largest angiosperm families. The family counts 41 domesticated crop species [19] whereof the majority is found within the Papilionoideae subfamily, namely within the hologalegnia and millettioid/phaseoloid clades which group the 'cool-season or temperate legumes' and the 'warm season or tropical legumes', respectively. Crop legumes play a central role in human health and nutrition. Their secondary metabolites are used for medical purposes and their protein rich seeds contribute to balanced diets especially in developing countries. Because of their ability to establish root nodules with nitrogen-fixing soil bacteria, legumes are of special interest for sustainable agriculture. Only 25% of the species within the basal subfamily Caesalpinioideae, and 90% in the Mi- mosoideae and Papilionoideae are nodule forming [20]. Lacking fossile evidence, we do not know when legumes began to associate with nodule-inducing bacteria, collectively called rhizobia. Their nod genes are induced after recognition of mostly flavonoid root exudates, leading to the expression of bacterial Nod-factors which stimulate further molecular com- munication. This results in the formation of infection threads by which rhizobia enter root tissues, the ultimate organogenesis of nodules and the differenciation of bacteria into bacte- rioids surrounded by a plant-derived membrane. The microsymbiont subsequently converts highly unreactive atmospheric N2 into a reduced form, amenable to the host's metabolism. The reaction of N2 to ammonia catalyzed by bacterial nitrogenase has a high energy de- mand and requires an environment of low oxygen concentration. Both prerequisites are provided by the plant host. The establishment of Arabidopsis thaliana as the first plant model organism, more than three decades ago, has been facilitating the investigation of complex biological processes. The development of the model legumes Lotus japonicus and M. truncatula started in the late 1990ies, primarily aiming at the study of plant-microbe interactions. Their genomes are now almost completely sequenced. Medicago truncatula Gaertn. is an important forage legume and has been additionally chosen as a model representative for cold season grain legumes, such as pea Pisum sativum, faba bean Vicia faba, lentil Lens culinaris, chickpea Cicer arietinum, and others. M. trun- catula combines convenient attributes for a plant model species: it is easily transformable and cultivable, it's autogamy results in abundant seed production, the genome is relatively small with ∼500Mb (compared to 5000Mb in pea [39]), it has a short reproductive cycle and it features high phenotypic plasticity. Up to date the M. truncatula genome is nearly 11 1. Introduction completely sequenced and the DFCI Medicago Gene Index comprises 268 712 expressed se- quence tags, which is an important condition for the straight-forward functional annotation of protein sequences. 1.2. Mass spectrometry-based proteomics Sessile organisms adapt to the environment trough biochemical processes: signals are trans- duced and perceived, the response is mediated via gene expression. Completed genome sequences and the outcome of numerous sequencing projects facilitate the analysis of gene products. Gene expression is addressed on two levels: the RNA and the protein level. Studying the dynamics of RNA (transcriptomics) provides information about the relative amounts of RNA, which are not necessarily proportional to levels of the encoded proteins [2]. This is all the more evident since proteins are present at a high dynamic range and are underlying mechanisms of synthesis, degradation and postranslational modifications. Thus studying proteomes is much closer to cellular function and plays a key role in our understanding of metabolic networks. A proteome is defined as the total set of proteins ex- pressed by a genome in a cell, tissue or organism [49, 53]. Since proteins are biochemically much more diverse than RNA, their large-scale identification and quantification requires analytical methods capable of dealing with their chemical properties and huge differences in protein concentration. Mass spectrometry, in combination with prefractionation and separation techniques, such as 2DE and HPLC-shotgun, are the most common and efficient tools at present. Since the invention of soft ionization methods MALDI (Matrix Assisted Laser Desorption) and ESI (Electrospray ionization) it became possible